Timeroom: Spring 2022

Displaying 301 - 310 of 460 Results for: Attributes = EUNH
Manchester   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 422 (M1) - Mathematics for Business Applications

Math for Business Applications

Online Course Delivery Method: Online with some campus visits, EUNH
Credits: 4.0
Term: Spring 2022 - UNHM Credit (15 weeks) (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   30  
CRN: 55299
Functions, sets and their use in mathematical models in business, economics and finance, including probability, linear systems and mathematics of finance; basic concepts of differential calculus and relevant applications.
You must sign up in the Dept Office before registering through WEBCAT.
Mutual Exclusion : MATH 420
Colleges not allowed in section: Paul College of Business&Econ
Attributes: Quantitative Reasoning(Disc)
Instructors: Donald Plante
Start Date End Date Days Time Location
1/25/2022 5/9/2022 R 1:01pm - 2:50pm PANDRA P101
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 732 (1ON) - Introduction to the R Software

Intro to the R Software

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 1.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Credit/Fail Grading
Class Size:   15  
CRN: 56488
This course provides a basic introduction to the open-sources statistical software R for students who have never used this software or have never formally learned the basics of it. Topics include: Numeric calculations, simple and advanced graphics, object management and work-flow, RStudio, user-contributed packages, basic programming, writing of functions, statistical modeling and related graphs, distributed computing, reproducible research and document production via markup language. Cr/F.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MATH 759
Instructors: Ernst Linder
Start Date End Date Days Time Location
1/25/2022 5/9/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 736 (1SY) - Advanced Statistical Modeling

Advanced Statistical Modeling

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 54828
This is a course on statistical models behind normal linear model. Topics covered in this course include generalized linear model, linear mixed model, generalized additive model, generalized linear mixed model, generalized additive mixed model, and smoothing methods if time allows. Prereq: MATH 739.
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Qi Zhang
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MWF 8:10am - 9:30am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 738 (1SY) - Data Mining and Predictive Analytics

Data Mining & Pred Analytics

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 52825
An introduction to supervised and unsupervised methods for exploring large data sets and developing predictive models. Unsupervised methods include: market basket analysis, principal components, clustering, and variables clustering. Important statistical and machine learning methods (supervised learning) include: Classification and Regression Trees (CART), Random Forests, Neural Nets, Support Vector Machines, Logistics Regression and Penalized Regression. Additional topics focus on metamodeling, validation strategies, bagging and boosting to improve prediction or classification, and ensemble prediction from a set of diverse models. Required case studies and projects provide students with experience in applying these techniques and strategies. The course necessarily involves the use of statistical software and programming languages. Undergraduate students are required to have junior or senior status to in enroll in this course. Prereq: MATH 539 (or MATH 644); or permission.
You must sign up in the Dept Office before registering through WEBCAT.
Mutual Exclusion : IT 630
Classes not allowed in section: Freshman, Sophomore
Instructors: Philip Ramsey
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MW 12:40pm - 2:00pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 740 (1ON) - Design of Experiments I

Design of Experiments I

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   75  
CRN: 51844
Course in design of experiments with applications to quality improvement in industrial manufacturing, engineering research and development, or research in physical and biological sciences. Experimental factor identification, statistical analysis and modeling of experimental results, randomization and blocking, full factorial designs, random and mixed effects models, replication and sub-sampling strategies, fractional factorial designs, response surface methods, mixture designs, and screening designs. Focuses on various treatment structures for designed experimentation and the associated statistical analyses. Use of statistical software. Prereq: MATH 539 (or 644); or permission.
You must sign up in the Dept Office before registering through WEBCAT.
Classes not allowed in section: Freshman
Instructors: Philip Ramsey
Start Date End Date Days Time Location
1/25/2022 5/9/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 740 (H01) - Design of Experiments I

Design of Experiments I\Honors

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 57664
Course in design of experiments with applications to quality improvement in industrial manufacturing, engineering research and development, or research in physical and biological sciences. Experimental factor identification, statistical analysis and modeling of experimental results, randomization and blocking, full factorial designs, random and mixed effects models, replication and sub-sampling strategies, fractional factorial designs, response surface methods, mixture designs, and screening designs. Focuses on various treatment structures for designed experimentation and the associated statistical analyses. Use of statistical software. Prereq: MATH 539 (or 644); or permission.
You must sign up in the Dept Office before registering through WEBCAT.
Attributes: Honors course
Instructors: Philip Ramsey
Start Date End Date Days Time Location
1/25/2022 5/9/2022 Hours Arranged ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 741 (1SY) - Survival Analysis

Survival Analysis

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 56498
Explorations of models and data-analytic methods used in medical, biological, and reliability studies. Event-time data, censored data, reliability models and methods, Kaplan-Meier estimator, proportional hazards, Poisson models, loglinear models. The use of statistical software, such as SAS, JMP, or R, is fully integrated into the course. Prereq: MATH 739. (Offered in alternate years in the spring semester.)
You must sign up in the Dept Office before registering through WEBCAT.
Instructors: Qi Zhang
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MWF 9:40am - 11:00am ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 756 (1SY) - Principles of Statistical Inference

Princpls Statistical Inference

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   15  
CRN: 50583
Introduces the basic principles and methods of statistical estimation and model fitting. One- and two-sample procedures, consistency and efficiency, likelihood methods, confidence regions, significance testing, Bayesian inference, nonparametric and re-sampling methods, decision theory. Prereq: MATH 755; or permission.
You must sign up in the Dept Office before registering through WEBCAT.
Classes not allowed in section: Freshman
Instructors: Linyuan Li
Start Date End Date Days Time Location
1/25/2022 5/9/2022 MWF 11:10am - 12:30pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 797 (1SY) - Senior Seminar

Senior Seminar

Online Course Delivery Method: Scheduled meeting time, Online (no campus visits), EUNH
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   20  
CRN: 52034
Exploration of mathematical topics beyond the student's previous coursework in the seminar format. The course focus is on independent research, collaborative work and classroom engagement; oral presentations and written work are required. Prereq: senior standing.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MATH 698
Only listed campus in section: Durham
Only listed classes in section: Senior
Only listed majors in section: AM:COMPUT, AM:DYNCNT, AM:FLUIDDYN, AM:SOLMECH, MATH (BA), MATH (BS)
Instructors: Marianna Shubov
Start Date End Date Days Time Location
1/25/2022 5/9/2022 TR 2:10pm - 4:00pm ONLINE
Durham   Engineering&Physical Sciences :: Mathematics&Statistics

MATH 832 (1ON) - Introduction to the R Software

Intro to the R Software

Online Course Delivery Method: Online (no campus visits), EUNH
Credits: 1.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Graduate Credit/Fail grading
Class Size:   15  
CRN: 56489
This course provides a basic introduction to the open-sources statistical software R for students who have never used this software or have never formally learned the basics of it. Topics include: Numeric calculations, simple and advanced graphics, object management and work-flow, RStudio, user-contributed packages, basic programming, writing of functions, statistical modeling and related graphs, distributed computing, reproducible research and document production via markup language. Cr/F.
You must sign up in the Dept Office before registering through WEBCAT.
Equivalent(s): MATH 859
Instructors: Ernst Linder
Start Date End Date Days Time Location
1/25/2022 5/9/2022 Hours Arranged ONLINE